Urban design and planning literature stresses the role of and need for meaningful urban public spaces for the experience of public life and social interaction. How to determine relationships between specific public places, their physical characteristics and the patterns of social activities they support, in order to promote meaningful innovation in terms of urban design and planning? How can we discover denizens’ perceptions that are affecting their urban experience? From what observations can we deduce what makes denizens satisfied? How do we get to situated everyday patterns, trends, social relations and possibilities? How can we see the relationships between these patterns and cultural and ethnic groups within and across cities?
Traditional data collection methods such as surveys, interviews, questionnaires and, more recently, data harvesting and analysis (e.g. on the use of mobile devices) have provided interesting insights on the social life of urban spaces. Recent technological development and the emergent participation of internet users in terms of social interaction, though, are leading us towards a redefinition of the possibilities of gathering and sharing first-hand information. Today virtually every denizen can produce and share public information about their everyday experiences and they actually do so, mostly using social networking services and website, such as Twitter, Facebook and Foursquare.
Can geo-referenced User Generated Content (UGC) shared over social online platforms be useful for the creation of meaningful, real time indicators of urban quality, as it is perceived and communicated by the citizens? Is it possible to use real-time text mining and conversational analysis methods on UGC in order to draw a series of maps depicting the very many and co-existing mental images of a city? How does an urban semantic layer - the meanings we attach to places - look like? How are well-being and happiness linked to places and how can we map them in real-time?
The paper presents a methodology and an experiment aiming to recognize multiple stories, as they emerge, influence each other, unfolding from city users’ mental representations and spatial experiences of city spaces, by conducting an analysis on location-based data sets extracted in real-time from UGC.
In particular how different ethnic groups are distributed spatially and temporally within the city of Milan and what are their sentiments towards the city spaces they name.